Personalisation of e-Learning Content via Metadata

A. Diab and H.-D. Wuttke (Germany)


Learning management systems,Adaptivity,User modeling,ontent metadata


The increasing importance of eLearning and its role in modernizing the teaching and learning methods can be seen from the huge amount of new offered eLearning courses and research projects. Although, new technologies and in particular the Internet has opened many new opportunities that are of a big interest for eLearning environments, these opportunities have not yet been exhausted. The current eLearning environments offer little or no support for adaptivity. Therefore, developing new adaptive eLearning environments that are able to satisfy the user’s requirements is of a big interest nowadays. This paper addresses the adaptivity issue and describes the architecture of a new Metadata-driven Adaptive eLearning Environment (MAeLE), which is a new framework for personalized adaptive eLearning. The basic principle of MAeLE depends on delivering adequate metadata for the user as well as for eLearning content. The eLearning content itself does not contain any sequence logic or metadata. User metadata are updated from time to time depending on the user’s behavior in the offered courses. The metadata correlate to the content metadata that mainly are defined in relation to the Learning Object Metadata (LOM) standard [16]. According to the user characteristics existing in the user model, the eLearning content, eLearning strategy and a navigation method are selected and updated from time to time correspondingly. A main advantage of MAeLE is its flexibility, extensibility and compatibility to the Sharable Content Object Reference Model (SCORM) [1], [18].

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